--- license: other configs: - config_name: hau data_files: - split: train path: hau/train-* - split: dev path: hau/dev-* - split: test path: hau/test-* - split: rejected path: hau/rejected-* - split: pending path: hau/pending-* - config_name: kau data_files: - split: train path: kau/train-* - split: dev path: kau/dev-* - split: test path: kau/test-* - split: rejected path: kau/rejected-* - split: pending path: kau/pending-* - config_name: shu data_files: - split: train path: shu/train-* - split: dev path: shu/dev-* - split: test path: shu/test-* - split: rejected path: shu/rejected-* - split: pending path: shu/pending-* dataset_info: - config_name: hau features: - name: id dtype: string - name: path dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: task_id dtype: int64 - name: sentence_source dtype: string - name: user_id dtype: string - name: age dtype: string - name: gender dtype: string - name: duration dtype: float64 - name: locale dtype: string - name: variant dtype: string - name: education_level dtype: string - name: country_of_origin dtype: string - name: created_at dtype: string splits: - name: train num_bytes: 14827524621.128 num_examples: 26996 - name: dev num_bytes: 1653234645.88 num_examples: 2540 - name: test num_bytes: 2887837588.52 num_examples: 4591 - name: rejected num_bytes: 782755135.265 num_examples: 1265 - name: pending num_bytes: 537930413.212 num_examples: 1273 download_size: 16023003452 dataset_size: 20689282404.005 - config_name: kau features: - name: id dtype: string - name: path dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: task_id dtype: int64 - name: sentence_source dtype: string - name: user_id dtype: string - name: age dtype: string - name: gender dtype: string - name: duration dtype: float64 - name: locale dtype: string - name: variant dtype: string - name: education_level dtype: string - name: country_of_origin dtype: string - name: created_at dtype: string splits: - name: train num_bytes: 11196364730.204 num_examples: 17149 - name: dev num_bytes: 2109040286.8 num_examples: 3485 - name: test num_bytes: 2079799640.24 num_examples: 3865 - name: rejected num_bytes: 2459403718.264 num_examples: 3044 - name: pending num_bytes: 127497059 num_examples: 180 download_size: 14242864227 dataset_size: 17972105434.508 - config_name: shu features: - name: id dtype: string - name: path dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: task_id dtype: int64 - name: sentence_source dtype: string - name: user_id dtype: string - name: age dtype: string - name: gender dtype: string - name: duration dtype: float64 - name: locale dtype: string - name: variant dtype: string - name: education_level dtype: string - name: country_of_origin dtype: string - name: created_at dtype: string splits: - name: train num_bytes: 4009726536.84 num_examples: 5702 - name: dev num_bytes: 429643651 num_examples: 657 - name: test num_bytes: 429377999 num_examples: 718 - name: rejected num_bytes: 95954787 num_examples: 134 - name: pending num_bytes: 679906469.768 num_examples: 1034 download_size: 4083273280 dataset_size: 5644609443.608 task_categories: - automatic-speech-recognition language: - ha - kr - ar size_categories: - 10K- :warning: This dataset is subject to access controls. To download the data, you must request access and accept the [Dataset Access Terms](https://huggingface.co/datasets/CLEAR-Global/TWB-Voice-dataset-access-terms). After approval, the dataset is provided under the terms of CC BY-NC 4.0. Note: These additional conditions mean this dataset is not a fully open dataset under Creative Commons licensing alone. By checking the box below, you confirm that: - You read and agree to the terms outlined in the Dataset Access Terms. - You understand that by downloading the dataset, you become a data controller, responsible for complying with applicable data protection laws, including acting on any data subject rights requests (such as deletion or correction). - If you redistribute this dataset, you will ensure that the recipients will use it under the same license and Dataset Access Terms. - In the event the dataset is updated in the future or if CLEAR Global receives a data deletion request, we will notify all registered downloaders. It is your responsibility as a data controller to implement such updates or deletions in your environment and other datasets that you might have distributed. extra_gated_fields: I have read and agree to the Dataset Access Terms: checkbox Would you be willing to be contacted by email in the future to provide brief feedback on how you have used this dataset?: type: select options: - Yes, I agree to be contacted for feedback - No, I do not wish to be contacted --- # TWB Voice Dataset v1.0 ## Dataset Summary TWB Voice 1.0 is a multilingual speech corpus containing read speech data in three languages from Nigeria: Hausa, Shuwa Arabic, and Kanuri. This dataset was created as part of the TWB Voice project by CLEAR Global (formerly Translators without Borders) to support automatic speech recognition (ASR) development for underrepresented languages. ## Languages - **Hausa (`hau`)**: Major language spoken in Nigeria, Niger, and neighboring regions. Also widely used as a lingua franca across West Africa - **Shuwa Arabic (`shu`)**: Variety of Arabic spoken by the Shuwa Arab people in the Lake Chad region - **Kanuri (`kau`)**: Language spoken around Lake Chad in Nigeria, Niger, Chad, and Cameroon ## Supported Tasks - **Automatic Speech Recognition (ASR)**: Primary intended use case. Our baseline models can be accessed at: - [Hausa Whisper-small fine-tuned](https://huggingface.co/CLEAR-Global/whisper-small-clearglobal-hausa-asr-1.0.0) - [Hausa Wav2Vec-Bert-2.0 fine-tuned](https://huggingface.co/CLEAR-Global/w2v-bert-2.0-clearglobal-hausa-asr-1.0.0) - [Kanuri Whisper-small fine-tuned](https://huggingface.co/CLEAR-Global/whisper-small-clearglobal-kanuri-asr-1.0.0) - [Kanuri Wav2Vec-Bert-2.0 fine-tuned](https://huggingface.co/CLEAR-Global/w2v-bert-2.0-clearglobal-kanuri-asr-1.0.0) - **Speaker Recognition**: Demographic metadata included for speaker analysis - **Language Identification**: Multi-language corpus suitable for language ID tasks - **Speech Synthesis**: Can also be used for TTS model training but you can also check our TTS-focused datasets for - [Hausa](https://huggingface.co/datasets/CLEAR-Global/TWB-voice-TTS-Hausa-1.0-sampleset) - [Kanuri](https://huggingface.co/datasets/CLEAR-Global/TWB-voice-TTS-Kanuri-1.0-sampleset) ## Dataset Structure ### Data Instances Each data instance contains: - Audio file path and audio data - Sentence text - Speaker demographic information (age range, gender, education level, country of origin) - Recording metadata ### Data Fields - `id`: Unique recording identifier - `path`: Audio file path - `sentence`: Read text prompt - `task_id`: Task identifier for the recorded text prompt - `sentence_source`: Source of the text content - `user_id`: Speaker identifier - `age`: Speaker age category (teens (18+), twenties, thirties, forties, fifties, sixties, seventies, over eighty) - `gender`: Speaker gender - `duration`: Audio duration in seconds - `locale`: Language code - `variant`: Language variant/dialect - `education_level`: Speaker’s education level - `country_of_origin`: Speaker’s country of origin - `created_at`: Recording timestamp ### Data Splits Each language configuration contains: - **train**: Training set (~80% of approved recordings) - **dev**: Development/validation set (~10% of approved recordings) - **test**: Test set (~10% of approved recordings) - **rejected**: Recordings that failed quality review - **pending**: Recordings awaiting quality review Splits are created to ensure no speaker overlap between train/dev/test sets while maintaining approximately 80/10/10 duration ratios. ## Dataset Statistics Hours summary by language and split: | | train | dev | test | total approved | pending | rejected | total collected | |:------|--------:|------:|-------:|-----------------:|----------:|-----------:|------------------:| | hau | 43.79 | 4.03 | 6.56 | 54.38 | 1.48 | 2.25 | 58.11 | | kau | 33.18 | 6.27 | 5.11 | 44.56 | 0.37 | 7.04 | 51.97 | | shu | 10.03 | 1.24 | 1.24 | 12.51 | 1.97 | 0.28 | 14.76 | | TOTAL | 87.00 | 11.54 | 12.91 | 111.45 | 3.81 | 9.57 | 124.84 | Hours approved by gender and language: | | male | female | total | |:------|-------:|---------:|--------:| | hau | 38.82 | 15.56 | 54.38 | | kau | 22.54 | 22.02 | 44.56 | | shu | 12.40 | 0.12 | 12.51 | | TOTAL | 73.76 | 37.70 | 111.45 | ## Usage ### Loading the Dataset ```python from datasets import load_dataset # Load specific language hausa_dataset = load_dataset("CLEAR-Global/twb-voice-1.0", "hau") shuwa_dataset = load_dataset("CLEAR-Global/twb-voice-1.0", "shu") kanuri_dataset = load_dataset("CLEAR-Global/twb-voice-1.0", "kau") # Load specific split train_data = load_dataset("CLEAR-Global/twb-voice-1.0", "hau", split="train") # Stream data for large datasets dataset = load_dataset("CLEAR-Global/twb-voice-1.0", "hau", streaming=True) ``` ## Dataset Creation ### Data Collection The dataset was collected through [TWB Voice platform](https://twbvoice.org/) coordinated by CLEAR Global. Native speakers were asked to read prompted text in their respective languages. ### Quality Control - All recordings, except for those in rejected and pending splits, underwent human review by native speakers. - Only approved recordings are included in train/dev/test splits - Rejected recordings and those pending for review are preserved in separate splits for analysis ## Ethical Considerations - All speakers consented to data collection and open publishing - Speaker identities are anonymized using user IDs - No attempts should be made to identify individual speakers - Data should be used responsibly for technology development ## Citation ```bibtex @dataset{twb_voice_2024, title = {TWB Voice 1.0}, author = {CLEAR Global}, year = {2024}, publisher = {Hugging Face}, url = {https://huggingface.co/datasets/CLEAR-Global/twb-voice-1.0} } ``` ## License The dataset is released under CC BY-NC 4.0 after approval under the [Dataset Access Terms](https://huggingface.co/datasets/CLEAR-Global/TWB-Voice-dataset-access-terms). Access is gated for compliance with privacy and data protection laws (e.g., GDPR). If your intended use of this dataset may be commercial in nature (such as building models into services that you monetize in any way), or you are unsure whether your use complies with the non-commercial restriction, especially for initiatives related to social good or public benefit, we encourage you to contact us to discuss potential licensing options or permissions. We are open to supporting impactful uses beyond the standard license terms. Contact us at tech@clearglobal.org, including a link to the dataset in question and a brief description of your intended use. ## Acknowledgments This dataset was created by CLEAR Global with support from the Patrick J. McGovern Foundation. ## Contact For questions about this dataset, please contact [CLEAR Global](mailto:info@clearglobal.org) or open an issue in the dataset repository.